In Silico Evaluation of Bilinear Elastoplastic Coronary Artery Stents
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Mechanical responses of the endovascular stent determine the arterial homeostasis and vulnerability of the atherosclerotic plaque. Given the various plaque components when the stent is deployed, the stent may apply excessive stress to the lesion and cause plaque rupture. Herein, using the interaction between the Palmaz–Schatz stent with two stent biomaterials, stainless steel, and magnesium alloy, and three different types of plaque, namely hypocellular, hypercellular, and calcified, are studied. An implicit finite element method is used to simulate and analyze the stress and strain acting on the stents, artery, and plaques. The Mooney–Rivlin hyperelastic material model is considered to study the responses of each component. The results reveal that stainless‐steel stents applied a higher level of stress to the plaques and vessel wall, which may lead to vascular damage and plaque rupture. However, a magnesium alloy stent with the similar design and geometrical parameters generates less stress on the plaque and artery. Interestingly, a minor improvement in magnesium alloy stents, increasing the strut thickness, can enhance the stent performance and lower the applied stresses to the vasculature and plaque, making them an ideal choice of material for stenting applications.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it